Peptides with the ability to spontaneously assemble into nanostructures of defined size, shape and chemical functionality are of tremendous interest, with potential biological, medical, electronic, photonic and nanotechnology applications. The enormous chemical sequence space which is available from 20 amino acids likely harbours many interesting candidates, including gelators, but it is currently not possible to predict supramolecular behaviour from sequence alone. Even for very short sequences (e.g. tripeptides), existing examples have been serendipitously discovered and largely limited to hydrophobic sequences, which form (nanoscale) aggregates, but lack the amphiphilicity required to gelate.
The use of very short peptides, pioneered by Gazit,5 is especially attractive, enhancing opportunities for rational design combined with robustness, scalability and cost reduction. Two main challenges are currently limiting the expansion of this field. Most examples of short peptides (<5 amino acids) that have been discovered since diphenylalanine (FF)5 contain only hydrophobic amino acids (vide infra). This is no surprise as hydrophobic interactions dominate self-assembly in water but it also limits their aqueous solubility and restricts applications. Secondly, in spite of two decades of intensive research since the first examples of short self-assembling peptides,6,7 most examples have been either discovered by serendipity or by mapping onto known sequence design rules from biological systems.3,4 
Experimentally, a small set of tripeptides has been reported to assemble into nanostructures in (mainly) aqueous environments, e.g. CFF forms nanospheres, FFF forms fibrous and plate-like assemblies;8,9 VFF, FFV and LFF form heterogeneous nanostructures;10-12 micelle formation was discovered in VYV13 and KFG,14 which in the latter case could reversibly be converted to nanotubes by lowering the pH; disordered aggregates were found upon drying of a solution of DFN.15 One common approach to alter the self-assembly properties of short peptides is protection of the terminal amine or acid groups, with acetyl,16,17 t-butyloxycarbonyl20,21 or large aromatic groups,18,19,22,23 reducing charge repulsions and introducing w-stacking/hydrophobic contributions to favour self-assembly and gelation. Simple rules have been described for assembling peptides based on repeating sequences based on biological systems. 24,25 However, gelators based on unprotected tripeptides are still elusive and only a small section of the available sequence space has been explored.
A number of researchers have recently studied molecular self-assembly in a supramolecular materials context using computational approaches.26,27 In previous work, we have shown that the propensity of dipeptides (two amino acids) to aggregate can be predicted using coarse-grain (CG) Molecular Dynamics (MD).28 Several other studies comprising short peptide fragments of biological relevance, such as NFGAIL16,29 (a fragment of human islet amyloid polypeptide) or FF,28,30 FFF31 and KLVFFAE32 (parts of amyloid β16-22), have shown the usefulness of CG-MD for studying peptide self-assembly. However, in all of these cases, the focus was on systems that were experimentally known to self-assemble, i.e. these examples are not predictive in nature.
Our earlier work was directed to the virtual screening of dipeptide aggregation and this allows virtual screening of all 400 dipeptides combinations. However, the ability of such a technique to screen tripeptides (8,000 in total) or larger peptides for their propensity to aggregate was not considered. As there are 8,000 tripeptides, it is impractical to synthesise and test all possible combinations for their ability to aggregate and it would be desirable to develop a virtual screening method to assist with this.
The present invention is based on an improved virtual screening method which allows all 8000 tripeptide sequences to be studied in a virtual manner and their propensity for aggregation to be estimated such that classes of peptides, such as tripeptides with certain properties that renders them most likely to form aggregates may be identified.
The screening method may be expanded to take account of how other parameters, such a pH, may affect peptide aggregation. A further aspect of the invention are the classes of peptides thus discovered themselves, as they show surprising, unprecedented and useful self-assembly behaviour, including gelation.
It is amongst the objects of the present invention to provide a method of virtual screening of peptides, such as tripeptides for their propensity to form aggregates in solution and optionally at a particular pH.